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GGUF
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imatrix
Instructions to use mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF:Q4_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF:Q4_K_M
Use Docker
docker model run hf.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF with Ollama:
ollama run hf.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF:Q4_K_M
- Unsloth Desktop
- Pi
How to use mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF with Docker Model Runner:
docker model run hf.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF:Q4_K_M
- Lemonade
How to use mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF:Q4_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF:Q4_K_M
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF:Q4_K_M" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
auto-patch README.md
Browse files
README.md
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| Link | Type | Size/GB | Notes |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF/resolve/main/Qwen3-4B-Thinking-2507-Esper3.1.imatrix.gguf) | imatrix | 0.1 | imatrix file (for creating your own qwuants) |
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Here is a handy graph by ikawrakow comparing some lower-quality quant
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types (lower is better):
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| Link | Type | Size/GB | Notes |
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|:-----|:-----|--------:|:------|
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF/resolve/main/Qwen3-4B-Thinking-2507-Esper3.1.imatrix.gguf) | imatrix | 0.1 | imatrix file (for creating your own qwuants) |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF/resolve/main/Qwen3-4B-Thinking-2507-Esper3.1.i1-IQ1_S.gguf) | i1-IQ1_S | 1.2 | for the desperate |
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| 92 |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF/resolve/main/Qwen3-4B-Thinking-2507-Esper3.1.i1-IQ1_M.gguf) | i1-IQ1_M | 1.2 | mostly desperate |
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| 93 |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF/resolve/main/Qwen3-4B-Thinking-2507-Esper3.1.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 1.3 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF/resolve/main/Qwen3-4B-Thinking-2507-Esper3.1.i1-IQ2_XS.gguf) | i1-IQ2_XS | 1.5 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF/resolve/main/Qwen3-4B-Thinking-2507-Esper3.1.i1-IQ2_S.gguf) | i1-IQ2_S | 1.5 | |
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| 96 |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF/resolve/main/Qwen3-4B-Thinking-2507-Esper3.1.i1-IQ2_M.gguf) | i1-IQ2_M | 1.6 | |
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| 97 |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF/resolve/main/Qwen3-4B-Thinking-2507-Esper3.1.i1-Q2_K_S.gguf) | i1-Q2_K_S | 1.7 | very low quality |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF/resolve/main/Qwen3-4B-Thinking-2507-Esper3.1.i1-Q2_K.gguf) | i1-Q2_K | 1.8 | IQ3_XXS probably better |
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| 99 |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF/resolve/main/Qwen3-4B-Thinking-2507-Esper3.1.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 1.8 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF/resolve/main/Qwen3-4B-Thinking-2507-Esper3.1.i1-IQ3_XS.gguf) | i1-IQ3_XS | 1.9 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF/resolve/main/Qwen3-4B-Thinking-2507-Esper3.1.i1-Q3_K_S.gguf) | i1-Q3_K_S | 2.0 | IQ3_XS probably better |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF/resolve/main/Qwen3-4B-Thinking-2507-Esper3.1.i1-IQ3_S.gguf) | i1-IQ3_S | 2.0 | beats Q3_K* |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF/resolve/main/Qwen3-4B-Thinking-2507-Esper3.1.i1-IQ3_M.gguf) | i1-IQ3_M | 2.1 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF/resolve/main/Qwen3-4B-Thinking-2507-Esper3.1.i1-Q3_K_M.gguf) | i1-Q3_K_M | 2.2 | IQ3_S probably better |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF/resolve/main/Qwen3-4B-Thinking-2507-Esper3.1.i1-Q3_K_L.gguf) | i1-Q3_K_L | 2.3 | IQ3_M probably better |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF/resolve/main/Qwen3-4B-Thinking-2507-Esper3.1.i1-IQ4_XS.gguf) | i1-IQ4_XS | 2.4 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF/resolve/main/Qwen3-4B-Thinking-2507-Esper3.1.i1-Q4_0.gguf) | i1-Q4_0 | 2.5 | fast, low quality |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF/resolve/main/Qwen3-4B-Thinking-2507-Esper3.1.i1-IQ4_NL.gguf) | i1-IQ4_NL | 2.5 | prefer IQ4_XS |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF/resolve/main/Qwen3-4B-Thinking-2507-Esper3.1.i1-Q4_K_S.gguf) | i1-Q4_K_S | 2.5 | optimal size/speed/quality |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF/resolve/main/Qwen3-4B-Thinking-2507-Esper3.1.i1-Q4_K_M.gguf) | i1-Q4_K_M | 2.6 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF/resolve/main/Qwen3-4B-Thinking-2507-Esper3.1.i1-Q4_1.gguf) | i1-Q4_1 | 2.7 | |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF/resolve/main/Qwen3-4B-Thinking-2507-Esper3.1.i1-Q5_K_S.gguf) | i1-Q5_K_S | 2.9 | |
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| 113 |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF/resolve/main/Qwen3-4B-Thinking-2507-Esper3.1.i1-Q5_K_M.gguf) | i1-Q5_K_M | 3.0 | |
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| 114 |
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| [GGUF](https://huggingface.co/mradermacher/Qwen3-4B-Thinking-2507-Esper3.1-i1-GGUF/resolve/main/Qwen3-4B-Thinking-2507-Esper3.1.i1-Q6_K.gguf) | i1-Q6_K | 3.4 | practically like static Q6_K |
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Here is a handy graph by ikawrakow comparing some lower-quality quant
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types (lower is better):
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